The UK Met Office Unified Model (UM) is employed by many weather forecasting agencies around the globe. This model is designed to run across spatial and time scales and known to produce skillful predictions for large-scale weather systems. However, the model has only recently begun running operationally at horizontal grid spacings of ∼1.5 km [e.g., at the UK Met Office and the Korea Meteorological Administration (KMA)]. As its microphysics scheme was originally designed and tuned for large-scale precipitation systems, we investigate the performance of UM microphysics to determine potential inherent biases or weaknesses. Two rainfall cases from the KMA forecasting system are considered in this study: a Changma (quasi-stationary) front, and Typhoon Sanba (2012). The UM output is compared to polarimetric radar observations in terms of simulated polarimetric radar variables. Results show that the UM generally underpredicts median reflectivity in stratiform rain, producing high reflectivity cores and precipitation gaps between them. This is partially due to the diagnostic rain intercept parameter formulation used in the one-moment microphysics scheme. Model drop size is generally both under- and overpredicted compared to observations. UM frozen hydrometeors favor generic ice (crystals and snow) rather than graupel, which is reasonable for Changma and typhoon cases. The model performed best with the typhoon case in terms of simulated precipitation coverage.

Pan Y. J.,M. Xue, and G. Q. Ge, 2016: Incorporating diagnosed intercept parameters and the graupel category within the ARPS cloud analysis system for the initialization of double-moment microphysics: Testing with a squall line over South China. Mon. Wea. Rev.,144, 371-392.

The UK Met Office Unified Model (UM) is employed by many weather forecasting agencies around the globe. This model is designed to run across spatial and time scales and known to produce skillful predictions for large-scale weather systems. However, the model has only recently begun running operationally at horizontal grid spacings of ∼1.5 km [e.g., at the UK Met Office and the Korea Meteorological Administration (KMA)]. As its microphysics scheme was originally designed and tuned for large-scale precipitation systems, we investigate the performance of UM microphysics to determine potential inherent biases or weaknesses. Two rainfall cases from the KMA forecasting system are considered in this study: a Changma (quasi-stationary) front, and Typhoon Sanba (2012). The UM output is compared to polarimetric radar observations in terms of simulated polarimetric radar variables. Results show that the UM generally underpredicts median reflectivity in stratiform rain, producing high reflectivity cores and precipitation gaps between them. This is partially due to the diagnostic rain intercept parameter formulation used in the one-moment microphysics scheme. Model drop size is generally both under- and overpredicted compared to observations. UM frozen hydrometeors favor generic ice (crystals and snow) rather than graupel, which is reasonable for Changma and typhoon cases. The model performed best with the typhoon case in terms of simulated precipitation coverage.